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Runtime error
| # %% | |
| import pandas as pd | |
| import numpy as np | |
| np.random.seed(24) | |
| df = pd.DataFrame({'A': np.linspace(1, 10, 10)}) | |
| df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))], | |
| axis=1) | |
| df.iloc[0, 2] = np.nan | |
| df['reaction_show'] = True | |
| df | |
| # %% | |
| s = '' | |
| for v in df.reaction_show: | |
| s += str(int(v)) | |
| s | |
| # %% | |
| s = '101100' | |
| g2p = '' | |
| for i in range(len(s)-1): | |
| # print(i, i+2, s) | |
| # print(s[0:2]) | |
| g2p += '1' if '1' in s[i:i+2] else '0' | |
| g2p | |
| # %% | |
| # import plotly.express as px | |
| from plotly.offline import init_notebook_mode, iplot | |
| import numpy as np | |
| init_notebook_mode() | |
| x = np.linspace(0, 1) | |
| iplot([{'x': x, 'y': 1-np.exp(-x)}]) | |
| # # def highlight_greaterthan(s,column): | |
| # # is_max = pd.Series(data=False, index=s.index) | |
| # # is_max[column] = s.loc[column] >= 1 | |
| # # return ['background-color: red' if is_max.any() else '' for v in is_max] | |
| # def highlight_greaterthan_1(s): | |
| # if s.B > 1.0: | |
| # return ['background-color: white']+['background-color: yellow']+['background-color: white']*3 | |
| # else: | |
| # return ['background-color: white']*5 | |
| # df.style.apply(highlight_greaterthan_1, axis=1) | |
| # %% | |
| from transformers import pipeline | |
| classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True) | |
| emotion = classifier("the sentence") | |
| # %% | |
| emotion[0] | |
| # %% | |
| emotion[0][0] | |
| # %% | |
| sorted(emotion[0], key=lambda x: x['score'], reverse=True) | |
| # %% | |
| import random | |
| values = [1,2, 3, 4, 5, 6] | |
| k = random.randint(0,len(values)) | |
| numbers = random.choices(values, k=k) | |
| print(k, "random numbers", numbers) | |
| # %% | |
| k = random.randint(0,len(values)) | |
| numbers = random.sample(values, k=k) | |
| print(k, "random numbers", numbers) | |
| # %% | |